2025
Structural equation models for multivariate extremes
Lausanne, EPFL, 2025.2024
Anthony C. Davison and Raphael de Fondeville’s contribution to the Discussion of ‘Inference for extreme spatial temperature events in a changing climate with application to Ireland’ by Healy et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS. 2024. Vol. 74, num. 2. DOI : 10.1093/jrsssc/qlae081.BAYESIAN MODELING OF INSURANCE CLAIMS FOR HAIL DAMAGE
Annals of Applied Statistics. 2024. Vol. 18, num. 4, p. 3091 – 3108. DOI : 10.1214/24-AOAS1925.Correlation of powers of Hüsler-Reiss vectors and Brown-Resnick fields, and application to insured wind losses
Extremes. 2024. DOI : 10.1007/s10687-023-00474-w.Anthony C Davison and Igor Rodionov’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas
Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2024. Vol. 86, num. 1. DOI : 10.1093/jrsssb/qkad118.Space-Time Extremes of Severe U.S. Thunderstorm Environments
Journal of the American Statistical Association. 2024. DOI : 10.1080/01621459.2024.2421582.Flexible Statistical Inference for Multivariate Extremes
Lausanne, EPFL, 2024.2023
Valerie Chavez-Demoulin, Anthony C Davison and Erwan Koch’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’
Journal Of The Royal Statistical Society Series A-Statistics In Society. 2023. Vol. 72, num. 4, p. 856 – 857. DOI : 10.1093/jrsssc/qlad051.Valerie Chavez-Demoulin, Anthony C Davison and Erwan Koch’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’
Journal Of The Royal Statistical Society Series C-Applied Statistics. 2023. Vol. 72, num. 4, p. 856 – 857. DOI : 10.1093/jrsssc/qlad051.Improved inference for a boundary parameter
Canadian Journal Of Statistics-Revue Canadienne De Statistique. 2023. DOI : 10.1002/cjs.11791.Timing and spatial selection bias in rapid extreme event attribution
Weather And Climate Extremes. 2023. Vol. 41, p. 100584. DOI : 10.1016/j.wace.2023.100584.Plant sterols and cholesterol metabolism are associated with five-year cognitive decline in the elderly population
Iscience. 2023. Vol. 26, num. 6, p. 106740. DOI : 10.1016/j.isci.2023.106740.Some Reminiscences of David Cox
HARVARD DATA SCIENCE REVIEW. 2023. num. 2. DOI : 10.1162/99608f92.85038493.Gradient boosting with extreme-value theory for wildfire prediction
Extremes. 2023. DOI : 10.1007/s10687-022-00454-6.Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems
Lausanne, EPFL, 2023.Spatiotemporal wildfire modeling through point processes with moderate and extreme marks
The Annals of Applied Statistics. 2023. Vol. 17, num. 1, p. 560 – 582. DOI : 10.1214/22-AOAS1642.Wind, Hail, and Climate Extremes: Modelling and Attribution Studies for Environmental Data
Lausanne, EPFL, 2023.2022
Causal modelling of heavy-tailed variables and confounders with application to river flow
Extremes. 2022. DOI : 10.1007/s10687-022-00456-4.A note on universal inference
Stat. 2022. Vol. 11, num. 1, p. e501. DOI : 10.1002/sta4.501.Downscaling of Historical Wind Fields over Switzerland Using Generative Adversarial Networks
Artificial Intelligence for the Earth Systems. 2022. Vol. 1, num. 4, p. e220018. DOI : 10.1175/AIES-D-22-0018.1.Space Oddity? A Statistical Formulation of Conjunction Assessment
Journal Of Guidance Control And Dynamics. 2022. DOI : 10.2514/1.G006282.Stochastic derivative estimation for max-stable random fields
European Journal Of Operational Research. 2022. Vol. 302, num. 2, p. 575 – 588. DOI : 10.1016/j.ejor.2021.12.026.Improved Inference On Risk Measures For Univariate Extremes
Annals Of Applied Statistics. 2022. Vol. 16, num. 3, p. 1524 – 1549. DOI : 10.1214/21-AOAS1555.Tail Risk Inference via Expectiles in Heavy-Tailed Time Series
Journal Of Business & Economic Statistics. 2022. DOI : 10.1080/07350015.2022.2078332.Functional peaks-over-threshold analysis
Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2022. DOI : 10.1111/rssb.12498.Influence of advanced footwear technology on sub-2 hour marathon and other top running performances
Journal Of Quantitative Analysis In Sports. 2022. Vol. 18, num. 1, p. 73 – 86. DOI : 10.1515/jqas-2021-0043.Ecological momentary assessment of emotional processing: An exploratory analysis comparing daily life and a psychotherapy analogue session
Counselling & Psychotherapy Research. 2022. Vol. 22, num. 2, p. 345 – 356. DOI : 10.1002/capr.12455.Spatiotemporal modelling of extreme wildfires and severe thunderstorm environments
Lausanne, EPFL, 2022.Is There a Cap on Longevity? A Statistical Review
Annual Review Of Statistics And Its Application. 2022. Vol. 9, p. 21 – 45. DOI : 10.1146/annurev-statistics-040120-025426.2021
Study protocol for the ETMED-L project: longitudinal study of mental health and interpersonal competence of medical students in a Swiss university using a comprehensive framework of empathy
Bmj Open. 2021. Vol. 11, num. 12, p. e053070. DOI : 10.1136/bmjopen-2021-053070.Wildlife trafficking via social media in Brazil
Biological Conservation. 2021. Vol. 265, p. 109420. DOI : 10.1016/j.biocon.2021.109420.Human mortality at extreme age
Royal Society Open Science. 2021. Vol. 8, num. 9, p. 202097. DOI : 10.1098/rsos.202097.Sub‐asymptotic motivation for new conditional multivariate extreme models
Stat. 2021. Vol. 10, num. 1, p. e401. DOI : 10.1002/sta4.401.Predicting involuntary hospitalization in psychiatry: A machine learning investigation
European Psychiatry. 2021. Vol. 64, num. 1, p. e48. DOI : 10.1192/j.eurpsy.2021.2220.Trends in the Extremes of Environments Associated with Severe US Thunderstorms
Journal Of Climate. 2021. Vol. 34, num. 4, p. 1259 – 1272. DOI : 10.1175/JCLI-D-19-0826.1.Practical issues with modeling extreme Brazilian rainfall
Brazilian Journal Of Probability And Statistics. 2021. Vol. 35, num. 1, p. 21 – 36. DOI : 10.1214/20-BJPS495.Multivariate extremes over a random number of observations
Scandinavian Journal Of Statistics. 2021. Vol. 48, num. 3, p. 845 – 880. DOI : 10.1111/sjos.12463.Estimating an extreme Bayesian network via scalings
Journal Of Multivariate Analysis. 2021. Vol. 181, p. 104672. DOI : 10.1016/j.jmva.2020.104672.Parameter estimation for discretely observed linear birth-and-death processes
Biometrics. 2021. Vol. 77, p. 186 – 196. DOI : 10.1111/biom.13282.Max-infinitely divisible models and inference for spatial extremes
Scandinavian Journal Of Statistics. 2021. Vol. 48, num. 1, p. 321 – 348. DOI : 10.1111/sjos.12491.2020
Special Issue: “Data Science versus Classical Inference: Prediction, Estimation, and Attribution”, honouring Prof. Brad Efron’s International Prize in Statistics in 2019 Discussion
International Statistical Review. 2020. Vol. 88, p. S70 – S72. DOI : 10.1111/insr.12410.The challenges of impact evaluation: Attempting to measure the effectiveness of community-based disaster risk management
International Journal of Disaster Risk Reduction. 2020. Vol. 49, p. 101732. DOI : 10.1016/j.ijdrr.2020.101732.Simultaneous autoregressive models for spatial extremes
Environmetrics. 2020. p. e2656. DOI : 10.1002/env.2656.An unethical optimization principle
Royal Society Open Science. 2020. Vol. 7, num. 7, p. 200462. DOI : 10.1098/rsos.200462.A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma
Plos Computational Biology. 2020. Vol. 16, num. 6, p. e1007882. DOI : 10.1371/journal.pcbi.1007882.A Global-Local Approach For Detecting Hotspots In Multiple-Response Regression
Annals Of Applied Statistics. 2020. Vol. 14, num. 2, p. 905 – 928. DOI : 10.1214/20-AOAS1332.Discussion
Journal Of The American Statistical Association. 2020. Vol. 115, num. 530, p. 663 – 664. DOI : 10.1080/01621459.2020.1762616.Strong convergence of multivariate maxima
Journal Of Applied Probability. 2020. Vol. 57, num. 1, p. 314 – 331. DOI : 10.1017/jpr.2019.100.Linking micro and macroevolution in the presence of migration
Journal Of Theoretical Biology. 2020. Vol. 486, p. 110087. DOI : 10.1016/j.jtbi.2019.110087.Inference on the Angular Distribution of Extremes
Lausanne, EPFL, 2020.2019
Exploration and Inference in Spatial Extremes Using Empirical Basis Functions
Journal Of Agricultural Biological And Environmental Statistics. 2019. Vol. 24, num. 4, p. 555 – 572. DOI : 10.1007/s13253-019-00359-1.Comment: Models Are Approximations!
Statistical Science. 2019. Vol. 34, num. 4, p. 584 – 590. DOI : 10.1214/19-STS746.Extinction In Lower Hessenberg Branching Processes With Countably Many Types
Annals Of Applied Probability. 2019. Vol. 29, num. 5, p. 2782 – 2818. DOI : 10.1214/19-AAP1464.A central limit theorem for functions of stationary max-stable random fields on R-d
Stochastic Processes And Their Applications. 2019. Vol. 129, num. 9, p. 3406 – 3430. DOI : 10.1016/j.spa.2018.09.014.A nonparametric method for producing isolines of bivariate exceedance probabilities
Extremes. 2019. Vol. 22, num. 3, p. 373 – 390. DOI : 10.1007/s10687-019-00348-0.Decompositions of dependence for high-dimensional extremes
Biometrika. 2019. Vol. 106, num. 3, p. 587 – 604. DOI : 10.1093/biomet/asz028.Fitting Markovian binary trees using global and individual demographic data
Theoretical Population Biology. 2019. Vol. 128, p. 39 – 50. DOI : 10.1016/j.tpb.2019.04.007.The time-dependent expected reward and deviation matrix of a finite QBD process
Linear Algebra And Its Applications. 2019. Vol. 570, p. 61 – 92. DOI : 10.1016/j.laa.2019.02.002.Spatial Risk Measures and Rate of Spatial Diversification
Risks. 2019. Vol. 7, num. 2, p. 52. DOI : 10.3390/risks7020052.A pathwise approach to the extinction of branching processes with countably many types
Stochastic Processes And Their Applications. 2019. Vol. 129, num. 3, p. 713 – 739. DOI : 10.1016/j.spa.2018.03.013.Extremal behaviour of aggregated data with an application to downscaling
Biometrika. 2019. Vol. 106, num. 1, p. 127 – 144. DOI : 10.1093/biomet/asy052.Geometric ergodicity for some space-time max-stable Markov chains
Statistics & Probability Letters. 2019. Vol. 145, p. 43 – 49. DOI : 10.1016/j.spl.2018.06.014.Genome-wide gene-based analyses of weight loss interventions identify a potential role for NKX6.3 in metabolism
Nature Communications. 2019. Vol. 10, p. 540. DOI : 10.1038/s41467-019-08492-8.Automatic L2 Regularization for Multiple Generalized Additive Models
Lausanne, EPFL, 2019.Contributions to Likelihood-Based Modelling of Extreme Values
Lausanne, EPFL, 2019.Large-scale variational inference for Bayesian joint regression modelling of high-dimensional genetic data
Lausanne, EPFL, 2019.Fast Automatic Smoothing for Generalized Additive Models
Journal Of Machine Learning Research. 2019. Vol. 20, p. 173.2018
Dependence properties of spatial rainfall extremes and areal reduction factors
Journal of Hydrology. 2018. Vol. 565, p. 711 – 719. DOI : 10.1016/j.jhydrol.2018.08.061.High-dimensional peaks-over-threshold inference
Biometrika. 2018. Vol. 105, num. 3, p. 575 – 592. DOI : 10.1093/biomet/asy026.‘The life of man, solitary, poore, nasty, brutish, and short’: Discussion of the paper by Rootzen and Zholud
Extremes. 2018. Vol. 21, num. 3, p. 365 – 372. DOI : 10.1007/s10687-018-0329-5.Automatic module selection from several microarray gene expression studies
BIOSTATISTICS. 2018. Vol. 19, num. 2, p. 153 – 168. DOI : 10.1093/biostatistics/kxx032.Optimal regionalization of extreme value distributions for flood estimation
JOURNAL OF HYDROLOGY. 2018. Vol. 556, p. 182 – 193. DOI : 10.1016/j.jhydrol.2017.10.051.Semiparametric Bayesian Risk Estimation for Complex Extremes
Lausanne, EPFL, 2018.Functional Peaks-Over-Threshold Analysis for Complex Extreme Events
Lausanne, EPFL, 2018.2017
Contributions to Modelling Extremes of Spatial Data
Lausanne, EPFL, 2017.Generalized Pickands constants and stationary max-stable processes
Extremes. 2017. Vol. 20, num. 3, p. 493 – 517. DOI : 10.1007/s10687-017-0289-1.Quasi-random numbers for copula models
Statistics And Computing. 2017. Vol. 27, num. 5, p. 1307 – 1329. DOI : 10.1007/s11222-016-9688-4.A Functional Framework for Enhanced Ultrasound Imaging
2017.Modelling across extremal dependence classes
Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2017. Vol. 79, num. 1, p. 149 – 175. DOI : 10.1111/rssb.12157.Extremal attractors of Liouville copulas
Journal of Multivariate Analysis. 2017. Vol. 160, p. 68 – 92. DOI : 10.1016/j.jmva.2017.05.008.Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures
Spatial Statistics. 2017. Vol. 21, p. 166 – 186. DOI : 10.1016/j.spasta.2017.06.004.Efficient inference for genetic association studies with multiple outcomes
Biostatistics. 2017. Vol. 18, num. 4, p. 618 – 636. DOI : 10.1093/biostatistics/kxx007.Robust Bounds In Multivariate Extremes
Annals Of Applied Probability. 2017. Vol. 27, num. 6, p. 3706 – 3734. DOI : 10.1214/17-Aap1294.2016
A Bayesian view of doubly robust causal inference
Biometrika. 2016. Vol. 103, num. 3, p. 667 – 681. DOI : 10.1093/biomet/asw025.Lyapunov Exponents for Branching Processes in a Random Environment: The Effect of Information
Journal Of Statistical Physics. 2016. Vol. 163, num. 2, p. 393 – 410. DOI : 10.1007/s10955-016-1474-3.A Levy-derived process seen from its supremum and max-stable processes
Electronic Journal Of Probability. 2016. Vol. 21, p. 14. DOI : 10.1214/16-Ejp1112.Exact simulation of max-stable processes
Biometrika. 2016. Vol. 103, num. 2, p. 303 – 317. DOI : 10.1093/biomet/asw008.The roles of coupling and the deviation matrix in determining the value of capacity in M/M/1/C queues
Queueing Systems. 2016. Vol. 83, num. 1-2, p. 157 – 179. DOI : 10.1007/s11134-016-9480-3.ODE parameter estimation through a runner’s model application
2016.A characterization of the normal distribution using stationary max-stable processes
Extremes. 2016. Vol. 19, num. 1, p. 1 – 6. DOI : 10.1007/s10687-015-0235-z.Bayesian Inference For The Brown-Resnick Process, With An Application To Extreme Low Temperatures
Annals of Applied Statistics. 2016. Vol. 10, num. 4, p. 2303 – 2324. DOI : 10.1214/16-Aoas980.Bayesian uncertainty management in temporal dependence of extremes
Extremes. 2016. Vol. 19, num. 3, p. 491 – 515. DOI : 10.1007/s10687-016-0258-0.Likelihood estimators for multivariate extremes
Extremes. 2016. Vol. 19, num. 1, p. 79 – 103. DOI : 10.1007/s10687-015-0230-4.2015
Extremal behavior of squared Bessel processes attracted by the Brown-Resnick process
Stochastic Processes And Their Applications. 2015. Vol. 125, num. 2, p. 780 – 796. DOI : 10.1016/j.spa.2014.09.006.Meta-analysis of incomplete microarray studies
Biostatistics. 2015. Vol. 16, num. 4, p. 686 – 700. DOI : 10.1093/biostatistics/kxv014.Max-stable processes and stationary systems of Levy particles
Stochastic Processes And Their Applications. 2015. Vol. 125, num. 11, p. 4272 – 4299. DOI : 10.1016/j.spa.2015.07.001.Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation
Journal Of The American Statistical Association. 2015. Vol. 110, num. 511, p. 1229 – 1238. DOI : 10.1080/01621459.2014.983230.Statistics of Extremes
Annual Review Of Statistics And Its Application; Palo Alto: Annual Reviews, 2015. p. 203 – 235.Objective Bayesian Model Selection
2015
A simple model-based approach to variable selection in classification and clustering
Canadian Journal Of Statistics-Revue Canadienne De Statistique. 2015. Vol. 43, num. 2, p. 157 – 175. DOI : 10.1002/cjs.11241.2014
Meta-analysis of Incomplete Microarray Studies
Lausanne, EPFL, 2014.Contributions to Spatial Statistics : Species Distributions and Rare Events
Lausanne, EPFL, 2014.Space-time modelling of extreme events
Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2014. Vol. 76, num. 2, p. 439 – 461. DOI : 10.1111/rssb.12035.Measuring the relative effect of factors affecting species distribution model predictions
Methods In Ecology And Evolution. 2014. Vol. 5, num. 9, p. 947 – 955. DOI : 10.1111/2041-210X.12203.Spectral Density Ratio Models for Multivariate Extremes
Journal Of The American Statistical Association. 2014. Vol. 109, num. 506, p. 764 – 776. DOI : 10.1080/01621459.2013.872651.Additive Smooth Modelling with Splines
2014
Efficient inference for spatial extreme value processes associated to log-Gaussian random functions
Biometrika. 2014. Vol. 101, num. 1, p. 1 – 15. DOI : 10.1093/biomet/ast042.Accurate Directional Inference for Vector Parameters in Linear Exponential Families
Journal Of The American Statistical Association. 2014. Vol. 109, num. 505, p. 302 – 314. DOI : 10.1080/01621459.2013.839451.Heavy-tail Phenomena: Spatio-temporal Extremal Dependence
2014
2013
From pointwise testing to a regional vision: An integrated statistical approach to detect nonstationarity in extreme daily rainfall. Application to the Sahelian region
Journal of Geophysical Research: Atmospheres. 2013. Vol. 118, num. 15, p. 8222 – 8237. DOI : 10.1002/jgrd.50340.On the relationship between total ozone and atmospheric dynamics and chemistry at mid-latitudes – Part 2: The effects of the El Nino/Southern Oscillation, volcanic eruptions and contributions of atmospheric dynamics and chemistry to long-term total ozone changes
Atmospheric Chemistry And Physics. 2013. Vol. 13, num. 1, p. 165 – 179. DOI : 10.5194/acp-13-165-2013.A Euclidean Likelihood Estimator for Bivariate Tail Dependence
Communications in Statistics – Theory and Methods. 2013. Vol. 42, num. 7, p. 1176 – 1192. DOI : 10.1080/03610926.2012.709905.Threshold modeling of extreme spatial rainfall
Water Resources Research. 2013. Vol. 49, num. 8, p. 4633 – 4644. DOI : 10.1002/wrcr.20329.Bayesian Semiparametrics for Modelling the Clustering of Extreme Values
2013.Statistical Modeling and Inference for Spatio-Temporal Extremes
Lausanne, EPFL, 2013.On the relationship between total ozone and atmospheric dynamics and chemistry at mid-latitudes – Part 1: Statistical models and spatial fingerprints of atmospheric dynamics and chemistry
Atmospheric Chemistry And Physics. 2013. Vol. 13, num. 1, p. 147 – 164. DOI : 10.5194/acp-13-147-2013.A new representation for multivariate tail probabilities
Bernoulli. 2013. Vol. 19, num. 5B, p. 2689 – 2714. DOI : 10.3150/12-Bej471.Geostatistics of Dependent and Asymptotically Independent Extremes
Mathematical Geosciences. 2013. Vol. 45, num. 5, p. 511 – 529. DOI : 10.1007/s11004-013-9469-y.Composite likelihood estimation for the Brown–Resnick process
Biometrika. 2013. Vol. 100, num. 2, p. 511 – 518. DOI : 10.1093/biomet/ass089.Spectral modeling of time series with missing data
Applied Mathematical Modelling. 2013. Vol. 37, num. 7, p. 4676 – 4684. DOI : 10.1016/j.apm.2012.09.040.Nonstationary Positive Definite Tapering On The Plane
Journal Of Computational And Graphical Statistics. 2013. Vol. 22, num. 4, p. 848 – 865. DOI : 10.1080/10618600.2012.729982.2012
High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust
Journal Of Statistical Software. 2012. Vol. 47, p. 1 – 22. DOI : 10.18637/jss.v047.i05.A case study of a “Dragon-King”: The 1999 Venezuelan catastrophe
European Physical Journal-Special Topics. 2012. Vol. 205, p. 131 – 146. DOI : 10.1140/epjst/e2012-01566-6.A dimension reduction technique for estimation in linear mixed models
2012. Conference of the LinStat, Tomar, PORTUGAL, Jul 27-31, 2010. p. 219 – 226. DOI : 10.1080/00949655.2011.604032.Extremes: spatial parametric modeling
Encyclopedia of Environmetrics Second Edition; Chichester, UK: John Wiley, 2012. p. 984 – 990.Statistical Analysis of Mountain Permafrost Temperatures
Lausanne, EPFL, 2012.Long-term changes in annual maximum snow depth and snowfall in Switzerland based on extreme value statistics
Climatic Change. 2012. Vol. 111, p. 705 – 721. DOI : 10.1007/s10584-011-0159-9.Extreme rainfall in West Africa: A regional modeling
Water Resources Research. 2012. Vol. 48, num. 8, p. W08501. DOI : 10.1029/2012Wr012052.Modelling Time Series Extremes
Revstat-Statistical Journal. 2012. Vol. 10, p. 109 – 133.Geostatistics of extremes
Proceedings of the Royal Society of London Series A: Mathematical and Physical Sciences. 2012. Vol. 468, p. 581 – 608. DOI : 10.1098/rspa.2011.0412.Serum antiglycan antibody detection of nonmucinous ovarian cancers by using a printed glycan array
International Journal Of Cancer. 2012. Vol. 130, p. 138 – 146. DOI : 10.1002/ijc.26002.Open Support Platform for Environmental Research (OSPER)-tools for the discovery and exploitation of environmental data
2012. AGU Fall Meeting.Diabetes imaging — quantitative assessment of islets of Langerhans distribution in murine pancreas using extended-focus optical coherence microscopy
Biomedical Optics Express. 2012. Vol. 3, num. 6, p. 1365 – . DOI : 10.1364/BOE.3.001365.Bayesian inference from composite likelihoods, with an application to spatial extremes
Statistica Sinica. 2012. Vol. 22, num. 2, p. 813 – 845. DOI : 10.5705/ss.2009.248.A generalization of the Solis-Wets method
Journal Of Statistical Planning And Inference. 2012. Vol. 142, p. 633 – 644. DOI : 10.1016/j.jspi.2011.08.016.Digging out the PPP hypothesis: an integrated empirical coverage
Empirical Economics. 2012. Vol. 42, p. 713 – 744. DOI : 10.1007/s00181-010-0441-0.Bivariate Extreme Statistics, Ii
Revstat-Statistical Journal. 2012. Vol. 10, p. 83 – 107.Tracking the US business cycle with a singular spectrum analysis
Economics Letters. 2012. Vol. 114, p. 32 – 35. DOI : 10.1016/j.econlet.2011.09.007.Anti-glycan antibodies in epithelial ovarian cancer
2012. p. S29 – S29.Statistical Modeling of Spatial Extremes
Statistical Science. 2012. Vol. 27, p. 161 – 186. DOI : 10.1214/11-STS376.Statistical modelling of ground temperature in mountain permafrost
Proceedings Of The Royal Society A-Mathematical Physical And Engineering Sciences. 2012. Vol. 468, p. 1472 – 1495. DOI : 10.1098/rspa.2011.0615.From sensor networks to connected analysis tools
2012. European Geosciences Union General Assembly 2012, Vienna, Austria, April 22-27, 2012.2011
Extreme temperature analysis under forest cover compared to an open field
Agricultural And Forest Meteorology. 2011. Vol. 151, p. 992 – 1001. DOI : 10.1016/j.agrformet.2011.03.005.Hierarchical wavelet modelling of environmental sensor data
Brazilian Journal of Probability and Statistics. 2011. Vol. 25, p. 406 – 420. DOI : 10.1214/11-BJPS154.Comparison of printed glycan array, suspension array and ELISA in the detection of human anti-glycan antibodies
Glycoconjugate Journal. 2011. Vol. 28, p. 507 – 517. DOI : 10.1007/s10719-011-9349-y.Statistics of extremes
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Annals of Applied Statistics. 2011. Vol. 5, p. 1699 – 1725. DOI : 10.1214/11-AOAS464.No benefit from combining HE4 and CA125 as ovarian tumor markers in a clinical setting
Gynecologic Oncology. 2011. Vol. 121, p. 487 – 491. DOI : 10.1016/j.ygyno.2011.02.022.Discussion of `Threshold modelling of spatially dependent non-stationary extremes with application to hurricane-induced wave heights’ by P. J. Northrop and P. Jonathan
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2011. International Statistical Institute, Dublin, Ireland, August 21-26, 2011.SpaCEM(3): a software for biological module detection when data is incomplete, high dimensional and dependent
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Curvature and Strength of Ni-YSZ Solid Oxide Half-cells after RedOx Treatments
Journal of Fuel Cells Science and Technology. 2010. Vol. 7, num. 5, p. 051011. DOI : 10.1115/1.4001019.Bayesian modelling for matching and alignment of biomolecules
The Oxford Handbook of Applied Bayesian Analysis; Oxford: Oxford University Press, 2010. p. 27 – 50.Likelihood-Based Inference for Max-Stable Processes
Journal of the American Statistical Association. 2010. Vol. 105, num. 489, p. 263 – 277. DOI : 10.1198/jasa.2009.tm08577.Effects of Rewarding and Unrewarding Experiences on the Response to Host-induced Plant Odors of the Generalist Parasitoid Cotesia marginiventris (Hymenoptera: Braconidae)
Journal of Insect Behavior. 2010. Vol. 23, num. 4, p. 303 – 318. DOI : 10.1007/s10905-010-9215-y.Comparison of Meta-analysis to Combined Analysis of a Replicated Microarray Study
Meta-analysis and Combining Information in Genetics; Chapman&Hall/CRC, 2010. p. 135 – 156.Extreme events in total ozone over Arosa—Part 2: Fingerprints of atmospheric dynamics and chemistry and effects on mean values and long-term changes
Atmospheric Chemistry And Physics. 2010. Vol. 10, p. 10033 – 10045. DOI : 10.5194/acp-10-10033-2010.Relationship between high daily erythemal UV doses, total ozone, surface albedo and cloudiness: An analysis of 30 years of data from Switzerland and Austria
Atmospheric Research. 2010. Vol. 98, p. 9 – 20. DOI : 10.1016/j.atmosres.2010.03.006.Geostatistics of Extremes : A Composite Likelihood Approach
Lausanne, EPFL, 2010.The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
Nature Biotechnology. 2010. Vol. 28, p. 827 – U109. DOI : 10.1038/nbt.1665.Extreme events in total ozone over Arosa—Part 1: Application of extreme value theory
Atmospheric Chemistry And Physics. 2010. Vol. 10, p. 10021 – 10031. DOI : 10.5194/acp-10-10021-2010.Mapping snow depth return levels: smooth spatial modeling versus station interpolation
Hydrology and Earth System Sciences. 2010. Vol. 14, num. 12, p. 2527 – 2544. DOI : 10.5194/hess-14-2527-2010.Revisiting the Edge, Ten Years On
Communications In Statistics-Theory And Methods. 2010. Vol. 39, p. 1674 – 1688. DOI : 10.1080/03610920902822670.Model misspecification in peaks over threshold analysis
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